Unintended consequences of atmospheric injection of sulphate aerosols.

Most climate scientists believe that climate geoengineering is best considered as a potential complement to the mitigation of CO{sub 2} emissions, rather than as an alternative to it. Strong mitigation could achieve the equivalent of up to -4Wm{sup -2} radiative forcing on the century timescale, relative to a worst case scenario for rising CO{sub 2}. However, to tackle the remaining 3Wm{sup -2}, which are likely even in a best case scenario of strongly mitigated CO{sub 2} releases, a number of geoengineering options show promise. Injecting stratospheric aerosols is one of the least expensive and, potentially, most effective approaches and for that reason an examination of the possible unintended consequences of the implementation of atmospheric injections of sulphate aerosols was made. Chief among these are: reductions in rainfall, slowing of atmospheric ozone rebound, and differential changes in weather patterns. At the same time, there will be an increase in plant productivity. Lastly, because atmospheric sulphate injection would not mitigate ocean acidification, another side effect of fossil fuel burning, it would provide only a partial solution. Future research should aim at ameliorating the possible negative unintended consequences of atmospheric injections of sulphate injection. This might include modeling the optimum rate and particle type and size of aerosol injection, as well as the latitudinal, longitudinal and altitude of injection sites, to balance radiative forcing to decrease negative regional impacts. Similarly, future research might include modeling the optimum rate of decrease and location of injection sites to be closed to reduce or slow rapid warming upon aerosol injection cessation. A fruitful area for future research might be system modeling to enhance the possible positive increases in agricultural productivity. All such modeling must be supported by data collection and laboratory and field testing to enable iterative modeling to increase the accuracy and precision of the models, while reducing epistemic uncertainties